Workshops

LATIS offers a series of workshops created by our experts that are free and open to all faculty and graduate students. Join our LATIS Research Workshops Google Group to be the first to learn about workshops. Joining the group is highly recommended as these workshops are popular and often fill to capacity. You can view the slides and materials from past workshops at the LATIS Workshop Materials website.

Spring 2020 Workshops

Workshops are generally held Fridays from 10am-12:30pm (check the Registration Page)

Introduction Nvivo - Jan 31

Introduction to R - Feb 7

Intro to ATLAS.ti - Feb 14

Rejuvenate your writing with Scrivener - Feb 28

Creating Professional Video Recordings for Media Projects - Introduction to LATIS Equipment - March 20

Data Management in transition: Strategies for when you graduate - April 10

Introduction to Computational Text Analysis - April 24

 

Workshop descriptions

 

Introduction to R

Register here for the workshop.

R is a popular tool for data analysis and statistical computing, and is a great alternative to tools like SPSS, Stata, or Excel. R is free and designed for reproducible research. This workshop will teach you how to get started using R to explore and clean your data. We will focus on issues social scientists often encounter when using data in R. 

This workshop will cover how to:

  • Create an R script (syntax/command file) to capture data cleaning steps in a reproducible way
  • Load a comma-delimited spreadsheet (.csv) into R as a dataset
  • View and examine data in R 
  • Check and correct missing values, rename variables, create new variables, and recode values in the data 
  • Save cleaned data file in formats for later use in R or other applications

To be successful, you should have:

 

Introduction to NVivo

Register here for the workshop.

NVivo is a qualitative data management, coding and markup tool, that facilitates powerful querying and exploration of source materials for both mixed methods and qualitative analysis. It integrates well with tools that assist in data collection and can handle a wide variety of source materials. This workshop introduces the basic functions of NVivo, with no prior experience necessary. The session is held in a computer lab with the software already installed. (Licensing is provided for faculty and graduate students of the College of Liberal Arts and the Humphrey School of Public Affairs.) 

This workshop will cover

  • Adding your source materials (text, images, audio/video, survey/spreadsheets)
  • Working with concepts (or codes/tags) and their definitions
  • Making annotations and analytical memos
  • Using text queries to speed up coding
  • Finding patterns in the concepts identified in the source materials
  • Importing data from other tools including Qualtrics, OneNote, and Zotero
  • Exporting excerpts and making backups
  • Working in teams

To be successful, you should

  • Be familiar with source materials used in qualitative research (interviews, focus groups, field notes, archival documents, etc.)
  • Be familiar with the types of questions asked in qualitative research

 

Intro to ATLAS.ti

Register here for the workshop.

ATLAS.ti is a qualitative analysis program, used to organize, tag, and analyze a variety of research materials including text, audio, and visual sources. It’s lineage is linguistic and discursive and provides a flexible workbench in which to conduct interpretive research, as well as other types of qualitative inquiry. This workshop introduces the basic functions of ATLAS.ti, with no prior experience necessary. It is held in a computer lab with the trial version of the software installed. (The full version of the software is provided by remote desktop for faculty and graduate students of the College of Liberal Arts, Carlson School of Management and the Humphrey School of Public Affairs.)

This workshop will cover

  • Adding your source materials (text, images, audio/video)
  • Working with codes (i.e. tags/themes/concepts)
  • Making annotations (comments) and analytical memos while linking them to sources
  • Using groups (of sources, codes, etc) to organize and segment materials
  • Performing searches using your codes
  • Exporting excerpts and making backups
  • Working in teams

To be successful, you should

  • Be familiar with source materials used in qualitative research (interviews, focus groups, field notes, archival documents, etc.)
  • Be familiar with the types of questions asked in qualitative research

 

Rejuvenate your writing with Scrivener

Register here for the workshop.
 
We often use our word processors as “slick typewriters” (according to research). But writing involves more than getting words on a page. Scrivener is a typewriter, a ring binder and a scrapbook, designed to support a variety of writing processes. In Scrivener, you can keep everything in one place: notes, outlines, drafts, edits. Scrivener is designed for writing in snippets, fleshing out sections as needed, jotting down new ideas. You can set goals, visualize how your writing project is structured, and move things around. Scrivener is ideal for writing projects large and small(er): dissertations, books and articles. You can use Scrivener to prepare presentations and lectures, whether singly or as a series. 

Through this workshop, you’ll learn about Scrivener and the writing process, and whether Scrivener is the right tool for your writing projects. 

About the software

Scrivener is not provided by or supported by OIT at the University of Minnesota. Scrivener is available for MacOS, Windows and iOS. An educational license costs about $40, and their (infrequent) upgrades are available at a discount. See the company website for more information. 

A free trial is available for 30 days of use. Participants are responsible for bringing a laptop with a trial or purchased version of Scrivener installed. 

This workshop will cover

  • Main features of Scrivener
  • Connections between Scrivener features and its environment and typical writing workflows
  • Opportunities to reflect on your own writing process and workflow
  • Similarities and differences between Scrivener, Microsoft Word, and Google Docs
  • Selecting the best writing tools for the job, given individual writing workflows and preferences

To be successful, you should have

  • An academic writing project, past or present, with writing and research materials available on your laptop or in the cloud. Your project can be at any stage (even finished). It helps to have an example project on hand for trying out features and thinking about your writing process. 
  • A laptop with Scrivener installed, either trial or paid version. 

 

Creating Professional Video Recordings for Media Projects - Introduction to LATIS Equipment

Register here for the workshop.

Video is an instantly engaging medium, as long as the presentation is of high enough quality to effectively convey your message without distractions. But how do you get better quality? We will demystify the settings and answer questions like “could I just use my smart phone,” or “why wouldn’t I use everything in auto mode?” This hands-on workshop will guide you through the steps of conducting a stationary interview with one subject to produce a high quality media recording. We will focus on a repeatable camera and lighting setup that can be a versatile approach for many different scenarios. You will be introduced to, and have hands on practice setting up and using the professional equipment available to you in the LATIS checkout center. This workshop will be helpful for those planning on developing media projects as a component of their research output. We will offer the option of staying until 2:00 to continue practicing set-ups.

This workshop will cover:

  • The basics of setting up camera, tripod, lighting and microphones 
  • The essential items - whether, and how to use auto or manual - for camera and sound
  • Connecting the microphone and setting the audio levels on the camera
  • A quick setup for interview lighting 
  • General tips for successful interviewing on camera

To be successful, you should have:

  • Wear closed toe shoes

 

Data Management in transition: Strategies for when you graduate

Register here for the workshop.

Research and creative work doesn't end with degree completion; however, access to many of the data storage tools and software that have supported that work changes when students become alumni. This workshop will help graduate students navigate questions about whether they can take their data and materials with them when they leave the university, and if so, how to do it. 

This workshop will cover:

  • The University policies that guide ownership of data
  • Access changes to storage, software, and services that happen upon graduation 
  • Strategies and tips for ensuring data are accessible and understandable long after graduation
  • How to make a plan to ensure a smooth transition for your data and materials between graduate school and your next endeavor

To be successful, you should:

  • Be a graduate student at the University of Minnesota at least a year into your program (it never hurts to plan early!), or who is nearing the end of your program. 
  • Have a research project (part of a dissertation or thesis) that has generated data or materials that you want to keep track of after you leave. This can include collaborative projects that will continue at UMN after graduation. 

Introduction to Computational Text Analysis

Register here for the workshop.

Scholars in humanities and social science fields are using computational tools to explore large corpora of digital texts. This hands-on workshop will introduce some common methods such as topic modeling and sentiment analysis, as well as fundamental cleaning and processing tasks for a text analysis workflow in Python.

This workshop will cover how to:

  • Read and write text files in Python
  • Manipulate ‘strings’ of text
  • Pre-process text for analysis (basic cleaning tasks such as normalizing case, stripping punctuation and whitespace, etc)
  • Count word frequencies
  • Create a document term matrix (a ‘bag of words’)
  • Build topic models and conduct sentiment analysis
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This workshop will also briefly introduce concepts and tools related to other common computational text analysis tasks: regular expressions (regex) and text cleaning, string matching and fuzzy matching, NLTK tools such as named entity recognition and parts-of-speech tagging, word embeddings (word2vec), classification tasks (e.g., stylometry, genre identification…)

To be successful, you should have:

  • A familiarity with textual data used in the social sciences
  • An intro-level familiarity with Python 
  • For an online introduction to Python see the Fall 2019 LATIS Python workshop recording and materials
  • or LinkedIn Learning’s Python Essentials
  • A laptop you can bring to the workshop
  • Optional: Install Python on your laptop (we recommend Anaconda).
  • There will be an online environment available for using Python, so local installation is not required.
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